Recent advancements in building automation and wireless sensors have made it possible to network whole building installations of previously autonomous devices (e.g. lights, wireless speakers and thermostats and household appliances). In many cases it is inefficient and undesirable to operate all of the devices at once (for example turning on all the lights when a person arrives home). Consequently, an active problem in building automation is to select a subset of devices (light, speakers etc.) that provide optimal performance, and dynamically adapts as the user moves throughout the building. For example, in the case of a network of wireless speakers, an automated system could endeavor to track a listener from room to room with music, such that the person receives approximately constant volume as they move about.
Controlling networks of building based devices in accordance with the dynamically changing locations of people or the occupancy of regions of a building is an ongoing challenge.
Modern homes and buildings can contain a multitude of short range wireless devices associated with the building (e.g. motion sensors or a WiFi enabled television). These are operable to transmit occupancy data about a region of a building. Central building controllers have been previously disclosed as devices to aggregate sensor data from a variety of building based sensors and devices (e.g. sensors, door locks, etc.) and to provide dynamic control over a subset of client devices (lights, speakers, screens, door, and appliances).
Several occupancy detection technologies (e.g. motion detectors, infrared, ultrasonic and sound detection) have been used by central controllers to determine occupancy of regions in buildings and control subsets of devices (e.g. automated lighting). However these technologies suffer from several drawbacks. One problem is that sensors such as PIR, motion, ultrasound or sound sensors are more effective at sensing the movement of a person rather than their location or identity. Another problem is that pets, trees and changes in heating and air-conditioning systems are known to cause false positive readings. Later, the addition of mobile wireless devices enabled indoor location systems to triangulate and estimate mobile device location. U.S. Pat. No. 8,102,784 and U.S. Pat. No. 7,843,333 describes systems to determine the location of mobile wireless sensors in a network of fixed wireless sensors with known position. The drawback with this approach for detecting the occupancy in a region of a building is the implicit assumption that the person and the mobile wireless device are always co-located.
More recently, mobile consumer wireless devices (smartphones, tablets and smartwatches and Bluetooth beacons) have been used as mobile location beacons. This is due in part to the inclusion of short range wireless transceivers (e.g., Bluetooth, BLE, WiFi and Zigbee). In many homes there is now a multitude of mobile wireless devices. Mobile wireless devices have considerable potential to improve occupancy detection and person location by central controllers.
U.S. Pat. No. 8,577,392 discloses a relay server that infers the location of a person, based on direct user-input activity at a plurality of devices associated with the person. U.S. Pat. No. 8,577,392 discloses devices associated with a person (e.g. personal wireless electronics) but does not account for the wide variety of fixed position wireless sensors, operable to indicate occupancy, associated with a building and not associated with a person (e.g. motion sensors and door sensors). U.S. Pat. No. 8,577,392 states mobile phones can be a strong predictor of people's location. While it is often the case that a person is in the same building as their mobile phone, this information is of very limited use to a central building controller, tasked with estimating real-time occupancy of various regions of the building. People often leave their phone and personal electronics (e.g. tablet PCs) in one room and travel to another, particularly in homes and offices. Thus mobile device location is an inconsistent predictor of people's location at the size scale needed for effective building automation.
Consumer wireless devices are often left unattended for periods of time and can therefore report misleading information regarding person location to a central controller. For example a person may arrive home and the position of their mobile phone may provide accurate indication of their location for a short period of time. Later the person may leave their mobile phone in one room and the mobile phone can report misleading occupancy data to the central controller. Thus the problem of automated control of electronic devices in response to a person's changing indoor location remains largely unsolved. In particular, no central controller previously disclosed has effectively combined fixed wireless sensor data with mobile wireless device location data, while addressing the erratic reliability of mobile device location data, to the task of determining the occupancy of regions of a building.